Bosch Manel, Kardash Elena
Scientific and Technological Centers (CCiTUB), Universitat de Barcelona, Barcelona, Spain.
BioEmergences Laboratory (USR 3695), CNRS, University Paris-Saclay, Gif-sur-Yvette, France.
Methods Mol Biol. 2019;2040:275-297. doi: 10.1007/978-1-4939-9686-5_13.
Genetically encoded FRET biosensors are powerful tools to visualize protein activity and signaling events in vivo. Compared with a biochemical approach, FRET biosensors allow a noninvasive spatial-temporal detection of signaling processes in live cells and animal tissues. While the concept of this technique is relatively simple, the experimental procedure is complicated and consists of several steps: (1) biosensor optimization; (2) data acquisition; and (3) image processing with each step posing its own challenge. In this chapter, we discuss steps (2) and (3) with the emphasis on the intramolecular RacFRET biosensor. We describe the design principle of the biosensor, the experimental imaging setup for acquiring FRET data in zebrafish embryos expressing the RacFRET biosensor, and the step-by-step ratio image generation protocol using Fiji software. We discuss important considerations during FRET data acquisition and analysis. Finally, we provide a macro code for the automated ratio image generation.
基因编码的荧光共振能量转移(FRET)生物传感器是在体内可视化蛋白质活性和信号事件的强大工具。与生化方法相比,FRET生物传感器能够对活细胞和动物组织中的信号传导过程进行非侵入性的时空检测。虽然这项技术的概念相对简单,但实验过程却很复杂,包括几个步骤:(1)生物传感器优化;(2)数据采集;(3)图像处理,每个步骤都有其自身的挑战。在本章中,我们将重点讨论分子内RacFRET生物传感器的步骤(2)和(3)。我们描述了生物传感器的设计原理、在表达RacFRET生物传感器的斑马鱼胚胎中获取FRET数据的实验成像设置,以及使用Fiji软件生成比率图像的逐步协议。我们讨论了FRET数据采集和分析过程中的重要注意事项。最后,我们提供了用于自动生成比率图像的宏代码。